In most causal problems we want to evaluate the long-term effects of policy changes but only have access to short-term experimental data. For example, for the long-term effects of minimum wage increase we may only have access to one-year worth of employment data. In this technical note we argue that such conceptual gap between what is to be estimated and what is in the data has not been adequately addressed. To make our criticism constructive we describe our approach in studying multiagent systems and the long-term effects of interventions in such systems. Central to our approach is behavioral game theory, where a behavioral model of how agents act conditional on their latent behaviors is combined with a temporal model of how behaviors evolve.